A comprehensive platform to manage peer churn and bandwidth fluctuations in real-time multimedia P2P networks

In the last few years, new service providers are growing in the Internet scenario to create new multimedia services. The most common approach to this end is based on peer-to-peer (P2P) networks. The new service providers are manifesting great interest not only for classical multimedia applications, like video streaming and video on demand, but also for multi-party games, private video-chat rooms, videoconference and real-time video teaching, usually containing a small number of high-interactive group members. The target of this paper is to define a multipoint multimedia communication platform for such kind of applications, accounting both peer set variation (peer arrivals and departures) and peer bandwidth modifications. In addition, a revenue model for providers of this kind of services is proposed to allow them to design their networks in order to maximize their revenue while satisfying user requirements in terms of both admission rejection probability and perceived quality on the received video stream.     

The ESTEEM platform: enabling P2P semantic collaboration through emerging collective knowledge

In this paper, we present Esteem (Emergent Semantics and cooperaTion in multi-knowledgE EnvironMents), a community-based P2P platform for supporting semantic collaboration among a set of independent peers, without prior reciprocal knowledge and no predefined relationships. Goal of Esteem is to go beyond the existing state-of-the-art solutions for P2P knowledge sharing and to provide an integrated platform for both data and service discovery. A distinguishing feature of Esteem is the use of semantic communities to explicitly give shape to the collective knowledge and expertise of peer groups with similar interests. Key techniques of Esteem will be presented in the paper and concern: shuffling-based communication, ontology and service matchmaking, context management, and quality-aware data integration. An application example of data and service discovery in the health-care domain will be presented, by also discussing results of system and user evaluation.     

Photodegradation of Anthracene and Benzo[a]anthracene in Polar and Apolar Media: New Pathways of Photodegradation

The photochemical reactions of anthracene and benzo[a]anthracene polycyclic aromatic hydrocarbons (PAHs) in polar and apolar solvents (cyclohexane and water/acetonitrile) were studied using spectroscopic and chromatographic techniques. These homogenous photolysis experiments are used as simplified models to compare PAHs photochemistry in water and oil (or oil films). Moreover, these processes were to some extent used as model in literature in order to study those occurring on particulate matter and aerosol surfaces. In both media, new photochemical reaction products were found. Generally, the reaction rate in the polar medium is faster than that in the apolar medium, and the photodegradation quantum yields increase with increasing polarity of the medium. HPLC-absorption/emission analysis confirmed the literature reports that mainly oxygenated photoproducts, such as PAH-hydroxides, were formed. The novelty of this article is that GC-MS data revealed the presence of new photoproducts that have not yet been described. This simplified model system allowed us to characterize the product distribution, thus simplifying the interpretation of the photodegradation mechanism. The identification of new photofragmentation paths, originating by irradiation of primary PAH photoproducts, may suggest an innovative way of remediation triggered by light.     

Multiscale modelling of the circulatory system: a preliminary analysis

In this paper we show how numerical solutions of human cardiovascular system may be devised by coupling models having different physical dimensions. One of the aspects of circulatory system is indeed its multiscale nature. Local flow features may have a global effect on circulation. For instance, a stenosis caused by an atherosclerotic plaque may change the overall characteristic of the vessels involved, and consequently have significant influence on the flow in the whole system. Hence, it lays the interest to set up a numerical device that could represent accurately both local and systemic features. For that, it is needed to couple different model scales. From lumped models (which are traditionally described by means of an electrical network analog) to local models based on 2D or 3D Navier-Stokes equations, passing through intermediate 1D models. In this paper, the different assumptions underlying these models, some mathematical issues related to their coupling and preliminary numerical results are presented. Received: 30 April 1999 / Accepted: 17 June 1999     

Ten challenges in modeling bibliographic data for bibliometric analysis

The complexity and variety of bibliographic data is growing, and efforts to define new methodologies and techniques for bibliometric analysis are intensifying. In this complex scenario, one of the most crucial issues is the quality of data and the capability of bibliometric analysis to cope with multiple data dimensions. Although the problem of enforcing a multidimensional approach to the analysis and management of bibliographic data is not new, a reference design pattern and a specific conceptual model for multidimensional analysis of bibliographic data are still missing. In this paper, we discuss ten of the most relevant challenges for bibliometric analysis when dealing with multidimensional data, and we propose a reference data model that, according to different goals, can help analysis designers and bibliographic experts in working with large collections of bibliographic data.     

Daily Depression and Cognitions About Stress: Evidence for a Traitlike Depressogenic Cognitive Style and the Prediction of Depressive Symptoms in a Prospective Daily Diary Study.

The authors examined the stability and dynamic structure of negative cognitions made to naturalistic stressors and the prediction of depressive symptoms in a daily diary study. Young adults reported on dispositional depression vulnerabilities at baseline, including a depressogenic cognitive style, dysfunctional attitudes, rumination, neuroticism, and initial depression, and then completed short diaries recording the inferences they made to the most negative event of the day along with their experience of depressive symptoms every day for 35 consecutive days. Daily cognitions about stressors exhibited moderate stability across time. A traitlike model, rather than a contextual one, explained this pattern of stability best. Hierarchical linear modeling analyses showed that individuals' dispositional depressogenic cognitive style, neuroticism, and their daily negative cognitions about stressors predicted fluctuations in daily depressive symptoms. Dispositional neuroticism and negative cognitive style interacted with daily negative cognitions in different ways to predict daily depressive symptoms. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of Iterative Methods for Solving a Ginzburg-Landau Equation

Very recently we have proposed to use a complex Ginzburg-Landau equation for high contrast inpainting, to restore higher dimensional (volumetric) data (which has applications in frame interpolation), improving sparsely sampled data and to fill in fragmentary surfaces. In this paper we review digital inpainting algorithms and compare their performance with a Ginzburg-Landau inpainting model. For the solution of the Ginzburg-Landau equation we compare the performance of several numerical algorithms. A stability and convergence analysis is given and the consequences for applications to digital inpainting are discussed.First online version published in June, 2005